Share:


Evaluation of UAV autonomous flight accuracy when classical navigation algorithm is used

    Ramūnas Kikutis Affiliation
    ; Jonas Stankūnas Affiliation
    ; Darius Rudinskas Affiliation

Abstract

This article examines and shows mathematical results of classical algorithm, which is used for small Unmanned Aerial Vehicle (UAV) navigation. The research is done with mathematical UAV model, which eliminates aerodynamics while the chosen flight path is followed by using vector field method. Lots of attention is dedicated to show possible flight path error values with representation of modelled flight path trajectories and deviations from the flight mission path. All of the modelled flight missions are done in two-dimensional space and all of the collected data with flight path error values are evaluated statistically. The most possible theoretical flight path error values are found and the general flight path error tendencies are predicted.

Keyword : navigation, algorithm, flight path error, small unmanned aerial vehicle, statistical evaluation, dynamic model

How to Cite
Kikutis, R., Stankūnas, J., & Rudinskas, D. (2018). Evaluation of UAV autonomous flight accuracy when classical navigation algorithm is used. Transport, 33(3), 589-597. https://doi.org/10.3846/transport.2018.2608
Published in Issue
Jul 10, 2018
Abstract Views
72
PDF Downloads
58
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Avellar, G. S. C.; Pereira, G. A. S.; Pimenta, L. C. A.; Iscold, P. 2015. Multi-UAV routing for area coverage and remote sensing with minimum time, Sensors 15(11): 27783–27803. https://doi.org/10.3390/s151127783

Beard, R. W.; Ferrin, J.; Humpherys, J. 2014. Fixed Wing UAV path following in wind with input constraints, IEEE Transactions on Control Systems Technology 22(6): 2103–2117. https://doi.org/10.1109/TCST.2014.2303787

Brezoescu, A.; Castillo, P.; Lozano, R. 2011. Straight-line path following in windy conditions, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 38(1/C22): 283–288. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-283-2011

Brezoescu, A.; Espinoza, T.; Castillo, P.; Lozano, R. 2013. Adaptive trajectory following for a fixed-wing UAV in presence of crosswind, Journal of Intelligent & Robotic Systems 69(1–4): 257–271. https://doi.org/10.1007/s10846-012-9756-8

Dadkhah, N.; Mettler, B. 2012. Survey of motion planning literature in the presence of uncertainty: considerations for UAV guidance, Journal of Intelligent & Robotic Systems 65(1–4): 233–246. https://doi.org/10.1007/s10846-011-9642-9

Kothari, M.; Postlethwaite, I.; Gu, D.-W. 2014. UAV path following in windy urban environments, Journal of Intelligent & Robotic Systems 74(3–4): 1013–1028. https://doi.org/10.1007/s10846-013-9873-z

Li, W.; Chen, W.; Wang, C.; Liu, M. Ge. Y.; Song, Q. 2015. A 3D path planning approach for quadrotor UAV navigation, in 2015 IEEE International Conference on Information and Automation, 8–10 August 2015, Lijiang, China, 2481–2486. https://doi.org/10.1109/ICInfA.2015.7279703

Nelson, D. R.; Barber, D. B.; McLain, T. W.; Beard, R. W. 2006. Vector field path following for small unmanned air vehicles, in 2006 American Control Conference, 14–16 June 2006, Minneapolis, MN, USA, 5788–5794. https://doi.org/10.1109/ACC.2006.1657648

Owen, M.; Beard, R. W.; Mclain, T. W. 2015. Implementing Dubins airplane paths on fixed-wing UAVs, in K. Valavanis, G. Vachtsevanos (Eds.). Handbook of Unmanned Aerial Vehicles, 1677–1701. https://doi.org/10.1007/978-90-481-9707-1_120

Wang, T.; Le Maître, O. P.; Hoteit, I.; Knio, O. M. 2016. Path planning in uncertain flow fields using ensemble method, Ocean Dynamics 66(10): 1231–1251. https://doi.org/10.1007/s10236-016-0979-2

Yeol, J. W.; Hwang, Y.-W. 2016. Parametrization of nonlinear trajectory for time optimal 2D path planning for unmanned aerial vehicles, in 2016 2nd International Conference on Control, Automation and Robotics (ICCAR), 28–30 April 2016, Hong Kong, China, 335–339. https://doi.org/10.1109/ICCAR.2016.7486751

Zhong, W.; Yan, L. 2014. A target visiting path planning algorithm for the fixed-wing UAV in obstacle environment, in 2014 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), 8–10 August 2014, Yantai, China, 2774–2778. https://doi.org/10.1109/CGNCC.2014.7007603